I build systems that pay for themselves.

I turn messy, manual work into automated, KPI-driven systems - data, full-stack, and ML. 10+ years end-to-end; now at St Catherine’s, Sydney.

10+ yrs
building software, data & AI systems end-to-end
2,000 users
pentested portal, shipped solo in 8 weeks
30K+
messages automated every month
1M+
client records managed in production

What I do

Software Engineering

Full-stack products shipped end-to-end - most recently a pentested portal serving 2,000 parents, built solo in 8 weeks.

Next.jsReactNode.jsGraphQLPythonTypeScript

Data Engineering

Pipelines, reporting and BI people trust - from reverse-engineering legacy ETL estates to dashboards leadership actually uses.

SQL ServerPostgreSQLPower BIApache SupersetETL

Automation & DevOps

I find manual work and delete it - a 100-minute batch job cut to ~2 seconds; deploy downtime from 10+ minutes to ~2s.

DockerGitHub ActionsCelery / RedisNginxSentry

AI / ML

Applied ML with honest metrics - deployed scikit-learn services, RAG assistants, and a 1,100+ commit open-source agentic pipeline.

scikit-learnFastAPIOpenAIClaudeRAG / agents

Core stack

Software

TypeScriptReactNext.jsNode.jsGraphQLPython

Data

SQL ServerPostgreSQLPower BIApache SupersetpandasRedis

Automation & DevOps

DockerGitHub ActionsCeleryNginxSentry

AI / ML

scikit-learnOpenAIClaudeRAGClaude Code / agents

Impact

Real, concrete results from systems I've built, scaled, and run - where there's a public write-up, the number links to it.

Reliability & security

0

Cross-account data leaks at 100-concurrent load

Passed

External OWASP pentest - no breach

500+

Automated tests behind a CI release gate

Efficiency

100 min → 2 s

Batch job runtime after a rewrite

~2 s

Deploy downtime, down from 10+ minutes

11 → 0

Manual query edits per finance reporting cycle

Timeline at a glance

Key career milestones and technical achievements

  1. 2023–2024

    Designed and launched Konquista, a Django + Celery/Redis WhatsApp automation platform powering 30K+ monthly messages across all clinics. Expanded Python expertise across FastAPI, Flask, and Streamlit for production-grade ML and automation pipelines.

  2. 2024

    Relocated to Sydney and continued delivering for international clients across time zones. Strengthened backend architecture, designed scalable Python systems, and completed Stanford’s Machine Learning Specialization.

  3. 2025

    Pursuing a Master’s in Software Engineering & AI while expanding full-stack capabilities. Shipped Wedstack (Next.js + GraphQL + Stripe), built AI tools on OpenAI, and published 30+ engineering write-ups on dev.to.

  4. 2026

    Joined St Catherine’s School, Sydney as a Data Analyst, now Data & Systems Specialist - building SQL Server pipelines, Power BI reporting, and cross-system integrations in a regulated educational environment, and laying data foundations for analytics and ML, while continuing the Master’s.